Precise Registration of Laser Mapping Data by Planar Feature Extraction for Deformation Monitoring
Precise Registration of Laser Mapping Data by Planar Feature Extraction for Deformation Monitoring
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DOI：
10.1109/tgrs.2018.2884712
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发表时间：
2019-06
影响因子：
8.2
通讯作者：
A. Kusari;C. Glennie;B. Brooks;T. Ericksen
中科院分区：
文献类型：
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作者：
A. Kusari;C. Glennie;B. Brooks;T. Ericksen
量化近场位移有助于更好地理解地震物理和灾害。迄今为止，建立遥感技术未能恢复亚厘米级近场位移的规模和分辨率所需的浅断层物理调查。在本文中，开发的方法来快速提取平面参数，使用快速并行的方法和一种替代的配准方法是自动匹配的平面提取成对的时间间隔移动的激光扫描（MLS）和机载激光扫描（ALS）数据集沿着纳帕故障。从两个时间间隔点云提取的特征，然后用于计算刚体变换参数。生产的强大和准确的变形地图需要选择适当的平面特征提取和特征映射标准。严格传播的点精度估计，以产生现实的估计误差的变换参数。从断层的左侧和右侧分别计算每个聚合研究区域的位移，并将其与对齐阵列位移的3 mm内进行比较。当地的差分位移显示出不同的模式，相比alinement阵列测量，被发现同意在置信范围内。研究结果表明，有能力准确地估计近场变形的重复MLS或ALS扫描地震多发的城市地区。ALS还与MLS数据集结合使用，说明该算法能够以亚厘米级精度适应不同的LiDAR收集模式。自动化的平面提取和配准是对近场地震动力学研究的重要贡献，可以用作未来地质反演模型的输入观测。
Quantifying near-field displacements can help enable a better understanding of earthquake physics and hazards. To date, established remote sensing techniques have failed to recover subcentimeter-level near-field displacements at the scale and resolution required for shallow fault physical investigations. In this paper, methods are developed to rapidly extract planar parameters, using fast parallel approaches and an alternative registration approach is employed to automatically match the planes extracted from pairwise temporally spaced mobile laser scanning (MLS) and Airborne laser scanning (ALS) data sets along the Napa fault. The features extracted from two temporally spaced point clouds are then used to calculate rigid-body transformation parameters. The production of robust and accurate deformation maps requires the selection of appropriate planar feature extraction and feature mapping criteria. Rigorously propagated point accuracy estimates are employed to produce realistic estimated errors for the transformation parameters. Displacements of each aggregate study area are computed separately from left and right sides of the fault and compared to be within 3 mm of alinement array displacements. Local differential displacements show distinct patterns which, compared to alinement array measurements, were found to agree within the confidence bounds. The findings demonstrate the ability to accurately estimate near-field deformations from repeated MLS or ALS scans of earthquake-prone urban areas. ALS is also used in conjunction with the MLS data sets, illustrating the algorithm’s ability to accommodate different LiDAR collection modalities at subcentimeter-level accuracy. The automated planar extraction and registration is an important contribution to the study of near-field earthquake dynamics and can be used as input observations for future geological inversion models.